Despite the prolific rise and alluring promise of large language-learning models in solving the climate crisis, their contributions to energy consumption and CO2 emissions through computational costs and data storage have only worsened these issues, with no clear signs of them aiding the climate in any significant, meaningful way. As exhibited by the data, the current trend of increasing pollution has shown no signs of changing, even after the creation of LLMs. We, as data scientists, are specialists in these fields--so, it is our responsibility to make this change, either through carefully navigating the training of LLMs or by crafting even greater solutions to their drawbacks. These tools are meant to aid the climate crisis, not worsen it.